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graph2tac

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1.0.4 graph2tac-1.0.4-py3-none-any.whl

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Project: graph2tac
Version: 1.0.4
Filename: graph2tac-1.0.4-py3-none-any.whl
Download: [link]
Size: 75957
MD5: 03b320e649f901c0903f25dc13aa618f
SHA256: 9591ce606fd540bf704924d42a174cebf95a1a699b0f3074c578f2d883820939
Uploaded: 2023-12-27 17:41:15 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: graph2tac
Version: 1.0.4
Summary: Train and run models which predict tactics for Coq.
Author: Lasse Blaauwbroek, Fidel I. Schaposnik Massolo, Miroslav Olšák, Vasily Pestun, Jason Rute
Project-Url: Homepage, https://github.com/IBM/graph2tac
Project-Url: Issues, https://github.com/IBM/graph2tac/issues
Project-Url: Repository, https://github.com/IBM/graph2tac
License: MIT
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: <3.12,>=3.9
Requires-Dist: keras (>=2.8)
Requires-Dist: tensorflow (<2.13,>=2.12.0)
Requires-Dist: tensorflow-gnn (<0.3,>=0.2.0)
Requires-Dist: protobuf (<4.0)
Requires-Dist: tqdm
Requires-Dist: numpy
Requires-Dist: pycapnp
Requires-Dist: psutil
Requires-Dist: pyyaml
Requires-Dist: graphviz
Requires-Dist: pytactician (==15.1)
Requires-Dist: pytest
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 4300 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.42.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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graph2tac/hash.py sha256=ngZ4ALbD_Uk5NzD25gH81c8K7UokPDg4SXjuIjLj85U 1360
graph2tac/predict.py sha256=pqbhLq__zZMzcWRLDlgW5jJFjgS_7hXz2FqxWl-AMJU 5327
graph2tac/loader/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
graph2tac/loader/data_classes.py sha256=u3AF_Tlg9db0XIUF1o_FCDAyXwwRIzMFNsY517_txd8 4193
graph2tac/loader/data_server.py sha256=s9jK3pWBlpz5sg3JWqlK-j4Gp8BhEi6g-x1DDpNXDv0 30605
graph2tac/loader/hmodel.py sha256=L7d26yU5OXxa85HDWqvOyiR2cNnwA1YnO9IDrAtCtE8 10048
graph2tac/loader/predict_server.py sha256=lEhwIf1aDNqzLvYupxj5vEPCRQmDi2BVHFHG6EB6OQI 40661
graph2tac/tfgnn/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
graph2tac/tfgnn/graph_schema.py sha256=Ec5Kfy6DgIcNJkwHeTem1CjkCk3Qp5_AeyfOBZ3ATJs 5713
graph2tac/tfgnn/metrics.py sha256=9I0d377zG-mReDqBqqYswm4tVt6KduCAMTVUdszC7xU 2372
graph2tac/tfgnn/models.py sha256=6iZmd19bkM94-n3vA5Cdpi-gToUPWCvISPrIdPW-u3M 47983
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graph2tac/tfgnn/predict.py sha256=FqiuwpwL8nT--H51Bxd-hu-KsL8nFdcVP8Ii-AY-wEc 38644
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graph2tac/tfgnn/tasks.py sha256=MIdJ7fKtbEg10LqyQYYobWrQ0sdXhWcTd9GhjbZf4vA 65698
graph2tac/tfgnn/train.py sha256=n9APhohEVerg2olX18HIvro8OSUbzSOZo_wrI2ZpORI 23426
graph2tac/tfgnn/train_utils.py sha256=5UWeSaj2Yv6UduCeljOZnlt7K_55qiZAYeK-oF96gsU 8411
graph2tac-1.0.4.dist-info/LICENSE sha256=xx0jnfkXJvxRnG63LTGOxlggYnIysveWIZ6H3PNdCrQ 11357
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graph2tac-1.0.4.dist-info/top_level.txt sha256=X28wyZgxwbUYEV03zj4ee7Y-pB_M73VxQ0CR-DiakKY 10
graph2tac-1.0.4.dist-info/RECORD — —

top_level.txt

graph2tac

entry_points.txt

[console_scripts]
g2t-server = graph2tac.loader.predict_server:main
g2t-tfgnn-predict-graphs = graph2tac.tfgnn.plot_predict_graphs:main
g2t-train-hmodel = graph2tac.loader.hmodel:main
g2t-train-tfgnn = graph2tac.tfgnn.train:main